Child Autism microbiome over time – Part 1

A reader granted permission to review their child with autism microbiome over time, especially in light of my recent post Technical Study on Autism Microbiome. It presents an opportunity to better understand the dynamics of the microbiome with autism. I say dynamic, because the microbiome keeps changing — sometimes in minor ways, other times major. It is a moving target. This is the first part of several posts. There is a lot of data and some of it caused me to write new tools to answer some questions that arose. I believe that microbiome has significant impact on the severity of symptoms in autism.

One time microbiome testing is foolishness… you need regular ongoing testing to discover what hangs around and what is a visitor passing thru… What hangs around is what is important… Visitors can often be ignored. The microbiome is very dynamic.

You don’t make a call on who going to win the next election by asking the first person you meet on the bus

Ken Lassesen

Timelines of Key Bacteria Taxa

Presentation of the material

Diversity

I find that Species reported often and be informative. Conventional wisdom is that more is better… There was a dramatic change in early 2019.

“Sample after probiotic L.reuterei and camel milk. Consistency soft solid
Diet: consisted of vegetable soups and also had introduced celery juice in the mornings”

Consensus Taxa

Prior post, Technical Study on Autism Microbiome cites:

The values are opposite – not high but very low.

Blautia being Low

Low values are the norm, often at the very bottom

Bifidobacterium being High (in some Published studies)

Usually low, but with two sudden spikes to high. This is reported low in some published studies and high in other studies. It may a volatile taxa with autism — I have seen major swings in another child with autism of Bifidobacterium.

Lactobacillus being High (in some Published studies)

Almost follows Bifidobacterium in flipping between low and high

Citizen Science Taxa

From most significant downwards..

Erysipelatoclostridium genus / Erysipelotrichia class / Erysipelotrichales order – Low

Clear match of pattern

Veillonella – High

Again agreement, with an increasing over time pattern

Senegalimassilia – High

With recent swings from none to high

Marvinbryantia – Low

Desulfovibrionales (Order) Low. This is reported in 92% of this lab’s sample. 6/11 having none is a low probability event.

Eggerthellales (Order) Low

Intestinimonas – Low

Was low and this year jumped

Anaerotruncus Low

Some random jumps but usually low

Pseudobutyrivibrio Low. This one is only seen 57% of the time in Thryve (which is what was used here) and 98% in uBiome. This distribution is not a very rare/unusual one like some following.

Burkholderiales Unusual!! Low and High (few middle ranges). Clicking the link I see 94% have measurable quantities – for only 1 out of 11 samples to have it is a 1 in 174,000,000,000 chance….

Deltaproteobacteria Low

Very high for a while and then collapse to nothing


Alistipes – Low. Clicking thru I see 85% have measurable quantities. For 7/11 samples having none (and when it does, very low)… suggests it’s absence may be significant.

Agreement

Borderline for Significance

Terrisporobacter Medium Low. Clicking this link I see 75% of samples have measurable amounts. For 10/11 samples to have none suggests some significance to its absence.

Breaks from the pattern

Summary Line #1

The following bacteria are rarely seen at all with this child but is very common in other samples. These are also reported as low across the Autism spectrum from Citizen Science:

The premise that we are working off it that the unusual is contributing to autism.

A good question to ask – Is this familial?

The mother has also done a Thryve sample so comparison was easy

Suggesting that it is unlikely due to DNA. It does suggests that giving the daughter a lot of kisses (especially on hands before meals) may have some benefits.. 😉

Suggestions #1: Dive down on this oddity

I went to Bacteria Symptom Explorer Plus (Autism via Citizen Science is there). And custom picked these 4 bacteria taxa that we want to increase. I then create a [Hand Picked Taxa Suggestion].

http://microbiomeprescription.azurewebsites.net/data/SymptomExplorer?includes=262&sampleId=
Our four taxa – all of these are low

We asked for 30 items, and got less – running with direct citations. It was interesting to see Triphala on the list because it reduces many bacteria and may as a consequence increase these!

Note that certain species of Bacillus and Bifidobacterium are good and others are bad!

I tried various ways of expanding suggestions and found only parents increased the list slightly. ß-glucan + linseed(flaxseed) + high fruit intake may translate to Iron-fortified Oat or Barley porridge with flaxseed and fruit for breakfast. Supper with Oregano, Turmeric with lots of cruciferous vegetables (broccoli cabbage)

Looking back at gut based on Suggestions

We look at the probiotics suggested and levels that this person have of then.

Thrive does not report on this one
Nor on this one
Nor this one
Eureka — we have one reporting
It comes and goes — mostly zero. Taking it makes sense
At the unspecified genus level this is a do not take a generic mixture of bifidobacterium

Predicted Symptoms

Going thru the samples, using 0.6 as the cut off point for predictions. Fatigue may manifest itself as irritability. Every single microbiome sample had autism as #1 predicted symptom.

The ouch!

The mother’s microbiome had a surprise… a weak autism-like profile. Only 12 matches (the daughter ranged from 14-21). The mother when she first emailed gave a “no health issue” description.

” Btw, I looked at the probable symptoms for my own sample and .. [many] were right on specially the neurocognitive ones… but a shocker at the blood type.. is 100%   Although none of the symptoms listed have ever been a concern, so sort of lived with it.. but now I’m so curious to exploring the data more.Thank you again for building this awesome tool!”

– Mother

This weekend I attended a conference with two presentations by Jason Hawrelak on Autism and the Microbiome. He presented his hypothesis that with modern western life, each generation’s microbiome becomes a subset of their parent’s microbiome. As a general concept, I agree if there are no radical changes of lifestyle (inconvenient changes usually). It’s a rational explanation for the increase of autism and other microbiome associated conditions. With this model, the mother was likely on the path towards autism(which was likely delivered to her by her mother) and with an additional iteration subsetting her microbiome… her child was dropped into it.

I believe that it is possible to recover significant amount of the lost microbiome. A simple first step is to spend weekends working on an organic farm as volunteer labor. If the kid eats dirt, or sucks on grass or wheat on this farm… he may be potentially repopulating some of the microbiome. I recall walking with my father (a farmer) and his picking straw and grass for me to suck on (unwashed) — I was getting hay bacillus or grass bacillus, a.k.a. Bacillus subtilis. “Farmer common sense medicine”

Next Installment

Coming next is Suggestions #2, looking at the bacteria that dominant the prediction of symptoms across the many samples, namely

  • Official Diagnosis: Autism
  • Comorbid: Constipation and Explosions (not diarrohea)
  • Official Diagnosis: Mast Cell Dysfunction

With these bacteria

NameRankTimes Cited
Dorea formicigeneransspecies33
Sutterellagenus33
Ruminococcaceaefamily30
Faecalibacteriumgenus27
Peptostreptococcaceaefamily27
Dorea longicatenaspecies26
Erysipelatoclostridiumgenus26
Fusicatenibactergenus24
Clostridialesorder24
Sutterellaceaefamily22

Please remember, I am not a medical professional. I am a professional statistician, artificial intelligence engineer and software developer (Microsoft, Amazon, Starbucks etc). I extracted “facts” from medical literature and use these facts to drive a fuzzy logic inference engine (commonly known as Artificial Intelligence).

The intent is to explore logical possibilities that may warrant future studies by medical professionals using statistics.